Bacterial Molecular Networks

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Bacterial Molecular Networks provides authoritative descriptions of various experimental and computational methods that enable the...

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Bacterial Molecular Networks provides authoritative descriptions of various experimental and computational methods that enable the characterization and analysis of molecular interaction networks.
Network-based representations have become pervasive in most fields in biology. Bacterial Molecular Networks: Methods and Protocols provides authoritative descriptions of various experimental and computational methods enabling the characterization and analysis of molecular interaction networks, with a focus on bacteria. Divided into three convenient sections, this volume provides extensive coverage of various experimental and in silico approaches aiming at the characterization of network components, addresses the presentation of computational approaches to analyze the topology of molecular networks, and further introduces a variety of methods and tools enabling scientists to generate qualitative or quantitative dynamical models of molecular processes in bacteria. Written in the highly successful Methods in Molecular Biology™ series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and accessible, Bacterial Molecular Networks: Methods and Protocols is intended primarily for post-graduate students and researchers working in the field of experimental and computational microbiology and provides a combination of up-to-date reviews along with detailed protocols written by the developers of bioinformatics resources, such as databases and software tools.
Includes cutting-edge methods and protocols Provides step-by-step detail essential for reproducible results Contains key notes and implementation advice from the experts Includes supplementary material: sn.pub/extras
Inhalt
1. Bacterial Molecular Networks: Bridging the Gap Between Functional Genomics and Dynamical Modeling Denis Thieffry, Ariane Toussaint, and Jacques van Helden Part I. Experimental and in silico approaches to unravel network components 2. Bacterial Interactomes: From Interactions to Networks Emmanuelle Bouveret and Christine Brun 3. From Bacterial to Microbial Ecosystems (Metagenomics) Shannon J. Williamson and Shibu Yooseph 4. Prokaryote Genome Fluidity: Towards a System Approach of the Mobilome Ariane Toussaint and Mick Chandler 5. Reticulate Classification of Mosaic Microbial Genomes using NeAT Website Gipsi Lima-Mendez 6. From Metabolic Reactions to Networks and Pathways Masanori Arita 7. Predicting Metabolic Pathways by Subnetwork Extraction Karoline Faust and Jacques van Helden 8. Directed Module Detection in a Large-scale Expression Compendium Qiang Fu, Karen Lemmens, Aminael Sanchez-Rodriguez, Inge M. Thijs, Pieter Meysman, Hong Sun, Ana Carolina Fierro, Kristof Engelen, and Kathleen Marchal 9. Using Phylogenetic Profiles to Predict Functional Relationships Matteo Pellegrini 10. Extracting Regulatory Networks of Escherichia coli from RegulonDB Heladia Salgado, Irma Martínez-Flores, Alejandra López-Fuentes, Jair Santiago García-Sotelo, Liliana Porrón-Sotelo, Hilda Solano, Luis Muniz-Rascado, and Julio Collado-Vides 11. Browsing Metabolic and Regulatory Networks with BioCyc Mario Latendresse, Suzanne Paley, and Peter D. Karp Part II. Topological analysis of bacterial networks 12. Algorithms for Systematic Identification of Small Sub-graphs Joseph Geraci, Geoffrey Liu, and Igor Jurisica 13. The Degree Distribution of Networks: Statistical Model Selection William P. Kelly, Piers J. Ingram, and Michael P. H. Stumpf 14. MAVisto: A Tool for Biological Network Motif Analysis Henning Schwöbbermeyer and Röbbe Wünschiers 15. Using MCL to Extract Clusters from Networks Stijn van Dongen and Cei Abreu-Goodger 16. Protein Complex Prediction with RNSC (Method) Andrew D. King, Nataa Prulj, and Igor Jurisica 17. Network Analysis and Protein Function Prediction with the PRODISTIN Web Site Anaïs Baudot, Ouissem Souiai and Christine Brun 18. Using the NeAT Toolbox to Compare Networks to Networks, Clusters to Clusters, and Networks to Clusters Sylvain Brohée 19. Analyzing Biological Data Using R: Methods for Graphs and Networks Nolwenn Le Meur and Robert Gentleman Part III. Dynamical Modelling 20. Detecting Structural Invariants in Biological Reaction Networks Jörn Behre, Luís Filipe de Figueiredo, Stefan Schuster, and Christoph Kaleta 21. Petri nets in Snoopy: A Unifying Framework for the Graphical Display, Computational Modelling, and Simulation of Bacterial Regulatory Networks Wolfgang Marwan, Christian Rohr, and Monika Heiner 22. Genetic Network Analyzer: A Tool for the Qualitative Modeling and Simulation of Bacterial Regulatory Networks Grégory Batt, Bruno Besson, Pierre-Emmanuel Ciron, Hidde de Jong, Estelle Dumas, Johannes Geiselmann, Regis Monte, Pedro T. Monteiro, Michel Page, François Rechenmann, and Delphine Ropers 23. Logical Modelling of Gene Regulatory Networks with GINsim Claudine Chaouiya, Aurélien Naldi, and Denis Thieffry 24. Modelling the Evolution of Mutualistic Symbioses Maren L. Friesen and Emily L. Jones 25. Modelling the Onset of Virulence in Pathogenic Bacteria Wilfred D. Kepseu, Frédérique Van Gijsegem, and Jacques-Alexandre Sepulchre 26. Spatial Stochastic Cellular Modeling with the Smoldyn Simulator Steven S. Andrews